Reaction Variety.
Linguistic markers have been found to be effective for early detection of rumors in social networks.
For example, Kwon et al.  [1]} demonstrated better detection performance of rumors on Twitter by using user and linguistic features rather than structural or temporal network features. Similarly, Zhao et al.  [2]} identified clusters of tweets that contain disputed claims by searching for fact-checking language.
Recently, Zhang et al.  [3]} classified Reddit comments into eight types including agreement, answer, appreciation, disagreement, elaboration, humor, negative reaction, and question, and analyzed patterns from these discussions arranged by various subreddits.
Our work goes one step further and employs information credibility classifiers like those mentioned above in order to better understand how (and how fast) human users and bots react to information posted by news sources of varying credibility.
